Midjourney Allcraft
Discover Midjourney Allcraft, your ultimate tool for advanced image generation and editing. Discover how this AI model can transform your workflow!
🚀Function Overview
Generates or edits images using text prompts, reference images, or masks, with LoRA support for style/object customization and adjustable parameters for resolution, aspect ratio, and generation speed.
Key Features
- Text-to-image generation via prompts
- Image-to-image transformations
- Inpainting with mask inputs
- LoRA scaling for style/object emphasis
- Multiple model modes (dev/schnell) for quality/speed trade-offs
- Adjustable resolution, aspect ratio, denoising steps, and safety checker
Use Cases
- •Creating digital artwork from text descriptions
- •Editing existing images via inpainting
- •Applying custom styles using LoRA models
- •Batch image generation
- •Rapid prototyping of visual concepts
⚙️Input Parameters
prompt
stringPrompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.
image
stringInput image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
mask
stringImage mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
aspect_ratio
stringAspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
height
integerHeight of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
width
integerWidth of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
prompt_strength
numberPrompt strength when using img2img. 1.0 corresponds to full destruction of information in image
model
stringWhich model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.
num_outputs
integerNumber of outputs to generate
num_inference_steps
integerNumber of denoising steps. More steps can give more detailed images, but take longer.
guidance_scale
numberGuidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5
seed
integerRandom seed. Set for reproducible generation
output_format
stringFormat of the output images
output_quality
integerQuality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
disable_safety_checker
booleanDisable safety checker for generated images.
go_fast
booleanRun faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
megapixels
stringApproximate number of megapixels for generated image
lora_scale
numberDetermines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
extra_lora
stringLoad LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
extra_lora_scale
numberDetermines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
💡Usage Examples
Example 1
Input Parameters
{ "model": "dev", "prompt": "a highly detailed cinematic closeup frontal portrait, humanoid robot with a reflective, dome-shaped head, contains a galaxy cosmos and nebula inside it, the robot's body, in shades of white, purple and black, features an array of textures and protrusions suggesting a complex internal structure, set against a soft-focus background with bokeh effect in cool blue tones, dark environment, moody and epic", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 38 }
Quick Actions
Technical Specifications
- Hardware Type
- H100
- Run Count
- 3.6k
- Commercial Use
- Unknown/Restricted
- Platform
- Replicate
Related Keywords
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